Tutorials, ideas, explanations, and resources
Tutorials
Series
How to Ultralearn Data Science
Data science toolbox
Concepts
Data Science | Machine Learning | Artificial Intelligence
Here is a list of the best free online courses on Data Science, Machine Learning, Deep Learning, and Artificial Intelligence.
Formal education in the 21st century has transformed into a choice instead of a mandatory step in life. With the internet boom and the rise of Massive Open Online Courses (MOOCs), one can opt for learning data science online and avoid the burden of student debt. Statistics show that eLearning enables students to learn 5x more material for every hour of training. The benefits of online learning are limitless — from the cost-cutting aspect to the flexible schedule and environment.
The democratization of Data Science
It’s the year 2020, and data science is more democratized than ever. This means any individual can do data science…
Data Engineering
The deep dive into the trend of Data Engineering and why it’s essential.
Data Engineering is the ‘real’ sexiest job in the 21st century. If you follow the data industry and are enthusiastic about the field, you may have seen or heard the term Data Engineering or the sexy title “Data Engineer” popping up everywhere.
If you’re curious about why and would like to dig deep into this topic, you’re in the right place!
My knowledge is limited, so I decided to ask this exact question on the r/dataengineering subreddit to understand this phenomenon.
With over 20 informative and helpful responses about this, below will be my attempt to summarise the main ideas…
Data Science
Can you use Machine Learning to predict which tweets will go viral?
In a previous article, I wrote about building an XGBoost model to predict video popularity for a past data science competition. It covered everything from loading the data and libraries to building the model itself.
Bitgrit has recently released a new competition with $3000 💵 up for grabs:
⭐ Viral Tweets Prediction Challenge ⭐
If you’ve ever wondered why tweets go viral, this is the perfect opportunity for you to find the answer using Data Science!
The competition ends on July 6, 2021, so sign up to get access to the data, and follow along with this article to get…
Deep Learning
ML Engineer, Sayak Paul presents key trends in Computer Vision
Computer Vision is a fascinating field of Artificial Intelligence that has tons of value in the real-world. There’s a huge wave of billion-dollar computer vision startups coming and Forbes expects the computer vision market to reach USD 49 billion by 2022.
The goal
The main goal of computer vision is to give computers the ability to understand the world through sight, and to make decisions based on their understanding.
In application, this technology allows the automation and augmentation of human sight, creating a myriad of use cases.
If AI enables computers to think, computer vision enables them to see, observe and understand…
Data Science
A short guide to time series forecasting using the Prophet library
Disclaimer: This article expresses thoughts and ideas that are mine alone and do not reflect the view of bitgrit. This article is for educational purposes only and should NOT be taken as financial advice.
The rise of cryptocurrencies
Cryptocurrency is a major topic of discussion recently as its market cap surged to a record $2 trillion in April 2021. To put that into comparison, the market cap of Apple, a 45 year old company has a market cap of around 2 trillion dollars as well.
If you don’t know about cryptocurrencies yet, it might be the time to start learning about them. They are…
Data Science
A guide to data cleaning using the Airbnb NY data set
It is widely known that data scientists spend a lot of their time cleaning data, you even might have heard that data scientists spend 80% of their time finding, cleaning, and reorganizing data, and only 20% analyzing it and producing insights.
What is Data Cleaning?
According the Wikipedia, Data Cleaning is:
the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.
From this definition, we can say that the aspects of…
Deep Learning
An easy step-by-step guide to building a convolutional neural network with PyTorch.
Look at the image above. What do you see? You might think this is a trivial question — clearly, it’s a yellow banana casting a shadow on a pink background. But how might computers recognize this image without having eyes and brains like humans do?
Computers aren’t able to infer about the world intuitively like we do, so for computers to “see” and recognize objects, scientists have to crack the complex system that is the human brain and implement it onto a computer. As children, we have an innate curiosity to explore and experiment with the world. …
Machine Learning
Exploring the most popular data science methods and their applications.
There are so many new data science algorithms and methods coming out every year that it can be overwhelming to learn all of them. Luckily, we have the State of Machine Learning and Data Science 2020 report, which was published by Kaggle in December last year, filled with statistics about Data Scientists from around the world including age breakdowns, educational background, programming skills, and salary information.
This article will focus on the most popular machine learning (ML) algorithms, explaining each method and the idea behind them while providing examples of their applications along with other helpful articles detailing the code…
Data Science
A thorough guide to building a simple XGBoost machine learning model for a data science competition.
The factors that determine whether a video goes viral are hard to narrow down, especially since popularity can be so subjective. What if we could use objective factors such as video metadata and thumbnails to predict how many views a video will get? This is the goal of the Video Popularity Prediction Challenge hosted on the data science competition platform Bitgrit.
In any data science competition, it’s important to start by posing some questions to better understand the problem, the goal, and the data you’re given. So, let’s start by asking these questions:
What is the goal?
The goal of this challenge is to…
